Data Processing Framework for Electric Vehicle-Generated Streams Using Hadoop

This paper constructs a data processing framework for massive data streams created from electric vehicle-related business models, such as vehicle tracking systems, charger status monitor systems, and vehicle sharing services. Hadoop is employed to cope with the size and heterogeneity of spatio-temporal streams, while PIG provides a data flow style script interface. Focused on the currently available state-of-charge streams and charger operation status records, our framework converts the stream into Hadoop-readable format and makes a PIG script filter a core subset essential for further analysis required by battery consumption modeling and power demand tracing. By this framework, we can explore the massive amount of data which will be collected from our electric vehicle service system, possibly making it possible to design a new sophisticated consumer-friendly information services.